Workload Indicators of Staffing Need (WISN) Method for Midwives Planning and Estimation at Asrade Zewude MemorialPrimary Hospital, North west Ethiopia

Abstract Background: Work force is a crucial component of health service delivery system. Ethiopia faces health workforce challenges with regard to evidence based health work force planning. First the health worker to population ratio was used and later standard staffing schedule for each health facility level was used. Both of these methods did not address the issue of evidence based workload variation between the same levels of facilities at different locations within a country. A workload indicator of staffing need (WISN) method addresses these variations. Therefore this study was done to determine the gaps or excess and workload pressure in midwives, thereby to promote on the use of WISN for health facilities based on WISN results of midwives at Asrade Zewude memorial Hospital. Methods: Cross sectional study using WISN model was used to determine the gaps or excess and workload pressure in midwives at Asrade Zewude Memorial primary hospital, North West Ethiopia. Midwives were selected based on priority point scale as outlined at WISN method. Results: The finding showed that there were five working days each week with 1030 hours actual working time per year for midwives. This working time was spent on health service activities (58.4%), additional activities (36.6%) and support activities (5%). WISN calculation showed that a shortage of five midwives with WISN ratio of 0.8 at Asrade Zewude Memorial primary hospital North West Ethiopia. Conclusion: Midwives at the study area were doing their routine work with 20% under staffed by covering the additional five midwives' position. With this working condition, it may be hard to achieve universal health coverage goals of the facility. Therefore the hospital should institutionalize WISN method planning to objectively employ midwifery professionals. This study had limitations too as it used retrospective annual service statistics and small sample size which affects generalization of the results to other health facilities and other health worker cadres within the study hospital.